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suppressPackageStartupMessages(library(tidyverse))
glimpse(storms)
## Observations: 10,010
## Variables: 13
## $ name        <chr> "Amy", "Amy", "Amy", "Amy", "Amy", "Amy", "Amy", "Am…
## $ year        <dbl> 1975, 1975, 1975, 1975, 1975, 1975, 1975, 1975, 1975…
## $ month       <dbl> 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 7, 7…
## $ day         <int> 27, 27, 27, 27, 28, 28, 28, 28, 29, 29, 29, 29, 30, …
## $ hour        <dbl> 0, 6, 12, 18, 0, 6, 12, 18, 0, 6, 12, 18, 0, 6, 12, …
## $ lat         <dbl> 27.5, 28.5, 29.5, 30.5, 31.5, 32.4, 33.3, 34.0, 34.4…
## $ long        <dbl> -79.0, -79.0, -79.0, -79.0, -78.8, -78.7, -78.0, -77…
## $ status      <chr> "tropical depression", "tropical depression", "tropi…
## $ category    <ord> -1, -1, -1, -1, -1, -1, -1, -1, 0, 0, 0, 0, 0, 0, 0,…
## $ wind        <int> 25, 25, 25, 25, 25, 25, 25, 30, 35, 40, 45, 50, 50, …
## $ pressure    <int> 1013, 1013, 1013, 1013, 1012, 1012, 1011, 1006, 1004…
## $ ts_diameter <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ hu_diameter <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
library("viridis")

ggplot(data=storms)+
  geom_jitter(aes(x= as.factor(month), y = pressure, fill = wind), pch = 21, alpha = 0.05)+
  scale_fill_viridis_c()+
  theme_bw()+
  labs(title= "Hurricane Pressure v Month", subtitle = "with Max Wind Speed", x = "Month")

Writing out equations in Rmarkdown:

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library(knitr)
kable(head(storms), caption = "Table using Kable")
Table using Kable
name year month day hour lat long status category wind pressure ts_diameter hu_diameter
Amy 1975 6 27 0 27.5 -79.0 tropical depression -1 25 1013 NA NA
Amy 1975 6 27 6 28.5 -79.0 tropical depression -1 25 1013 NA NA
Amy 1975 6 27 12 29.5 -79.0 tropical depression -1 25 1013 NA NA
Amy 1975 6 27 18 30.5 -79.0 tropical depression -1 25 1013 NA NA
Amy 1975 6 28 0 31.5 -78.8 tropical depression -1 25 1012 NA NA
Amy 1975 6 28 6 32.4 -78.7 tropical depression -1 25 1012 NA NA 
htmlTable::htmlTable(head(storms))
name year month day hour lat long status category wind pressure ts_diameter hu_diameter
1 Amy 1975 6 27 0 27.5 -79 tropical depression -1 25 1013
2 Amy 1975 6 27 6 28.5 -79 tropical depression -1 25 1013
3 Amy 1975 6 27 12 29.5 -79 tropical depression -1 25 1013
4 Amy 1975 6 27 18 30.5 -79 tropical depression -1 25 1013
5 Amy 1975 6 28 0 31.5 -78.8 tropical depression -1 25 1012
6 Amy 1975 6 28 6 32.4 -78.7 tropical depression -1 25 1012 
#make an interactive table
DT::datatable(storms)
## Warning in instance$preRenderHook(instance): It seems your data is too
## big for client-side DataTables. You may consider server-side processing:
## https://rstudio.github.io/DT/server.html
library(plotly)
## 
## Attaching package: 'plotly'
## The following object is masked from 'package:ggplot2':
## 
##     last_plot
## The following object is masked from 'package:stats':
## 
##     filter
## The following object is masked from 'package:graphics':
## 
##     layout
ggplotly(ggplot(data=storms)+
  geom_jitter(aes(x= as.factor(month), y = pressure, fill = wind), pch = 21, alpha = 0.05)+
  scale_fill_viridis_c()+
  theme_bw()+
  labs(title= "Hurricane Pressure v Month", subtitle = "with Max Wind Speed", x = "Month"))
## Warning in L$marker$color[idx] <- aes2plotly(data, params, "fill")[idx]:
## number of items to replace is not a multiple of replacement length